Generative AI Engineer

Role: LLM Scientist/Engineer

Position Type: Full-Time Contract (40hrs/week)

Contract Duration: Long Term

Work Schedule: 8 hours/day (Mon-Fri)

Location: 100% Remote

We are seeking an experienced LLM Engineer to design, develop, optimize, and deploy AI solutions using Large Language Models, with a strong focus on Retrieval Augmented Generation (RAG).

The ideal candidate will have strong Python and AI/ML development experience, hands-on expertise with LLMs, RAG pipelines, vector databases, prompt engineering, and agent-based frameworks, along with experience building API-driven AI solutions on AWS.

Key Responsibilities

• Design and develop RAG-based LLM applications and information retrieval pipelines.
• Develop AI/ML solutions using Python and modern NLP/LLM technologies.
• Work with AWS Bedrock and LLM models to develop production-ready AI solutions.
• Build and optimize embeddings, vector search, and retrieval pipelines.
• Develop agent-based applications using frameworks such as LangChain.
• Perform prompt engineering and LLM fine-tuning for business-specific use cases.
• Build API-driven architectures for AI products and services.
• Collaborate with stakeholders to understand business requirements and translate them into AI solutions.
• Use ML frameworks such as PyTorch, TensorFlow, and Hugging Face.
• Apply Docker, Kubernetes, and CI/CD practices for AI application deployment.
• Communicate technical architectures and AI/data flows clearly to technical and business stakeholders.

Required

• 3+ years of Python experience.
• 3+ years of ML/AWS experience.
• 1+ year of hands-on NLP/LLM experience.
• Strong RAG experience.
• AWS Bedrock experience.
• LangChain or similar LLM/agent framework.
• Vector databases and embeddings.
• Prompt engineering and LLM fine-tuning.
• PyTorch, TensorFlow, or Hugging Face.
• Docker/Kubernetes and CI/CD exposure.
• Excellent communication skills.